IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v465y2017icp261-276.html
   My bibliography  Save this article

Refined composite multivariate generalized multiscale fuzzy entropy: A tool for complexity analysis of multichannel signals

Author

Listed:
  • Azami, Hamed
  • Escudero, Javier

Abstract

Multiscale entropy (MSE) is an appealing tool to characterize the complexity of time series over multiple temporal scales. Recent developments in the field have tried to extend the MSE technique in different ways. Building on these trends, we propose the so-called refined composite multivariate multiscale fuzzy entropy (RCmvMFE) whose coarse-graining step uses variance (RCmvMFEσ2) or mean (RCmvMFEμ). We investigate the behavior of these multivariate methods on multichannel white Gaussian and 1/f noise signals, and two publicly available biomedical recordings. Our simulations demonstrate that RCmvMFEσ2 and RCmvMFEμ lead to more stable results and are less sensitive to the signals’ length in comparison with the other existing multivariate multiscale entropy-based methods. The classification results also show that using both the variance and mean in the coarse-graining step offers complexity profiles with complementary information for biomedical signal analysis. We also made freely available all the Matlab codes used in this paper.

Suggested Citation

  • Azami, Hamed & Escudero, Javier, 2017. "Refined composite multivariate generalized multiscale fuzzy entropy: A tool for complexity analysis of multichannel signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 261-276.
    • Handle: RePEc:eee:phsmap:v:465:y:2017:i:c:p:261-276
    DOI: 10.1016/j.physa.2016.07.077
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437116305404
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2016.07.077?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Silva, Luiz Eduardo Virgilio & Cabella, Brenno Caetano Troca & Neves, Ubiraci Pereira da Costa & Murta Junior, Luiz Otavio, 2015. "Multiscale entropy-based methods for heart rate variability complexity analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 422(C), pages 143-152.
    2. Gao, Zhong-Ke & Ding, Mei-Shuang & Geng, He & Jin, Ning-De, 2015. "Multivariate multiscale entropy analysis of horizontal oil–water two-phase flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 417(C), pages 7-17.
    3. Wu, Shuen-De & Wu, Chiu-Wen & Lee, Kung-Yen & Lin, Shiou-Gwo, 2013. "Modified multiscale entropy for short-term time series analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5865-5873.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wang, Yalin & Xu, Yan & Liu, Minghui & Guo, Yao & Wu, Yonglin & Chen, Chen & Chen, Wei, 2022. "Cumulative residual symbolic dispersion entropy and its multiscale version: Methodology, verification, and application," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Han, Yun-Feng & Jin, Ning-De & Zhai, Lu-Sheng & Ren, Ying-Yu & He, Yuan-Sheng, 2019. "An investigation of oil–water two-phase flow instability using multivariate multi-scale weighted permutation entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 518(C), pages 131-144.
    2. Deka, Bhabesh & Deka, Dipen, 2022. "An improved multiscale distribution entropy for analyzing complexity of real-world signals," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    3. Zhang, Ningning & Lin, Aijing & Ma, Hui & Shang, Pengjian & Yang, Pengbo, 2018. "Weighted multivariate composite multiscale sample entropy analysis for the complexity of nonlinear times series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 595-607.
    4. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Huang, Xuan, 2015. "Identifying the multiscale impacts of crude oil price shocks on the stock market in China at the sector level," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 434(C), pages 13-24.
    5. Alves Xavier, Sílvio Fernando & Xavier, Érika Fialho Morais & Jale, Jader Silva & Stosic, Tatijana & Santos, Carlos Antonio Costa dos, 2021. "Multiscale entropy analysis of monthly rainfall time series in Paraíba, Brazil," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    6. Zhai, Lu-Sheng & Zong, Yan-Bo & Wang, Hong-Mei & Yan, Cong & Gao, Zhong-Ke & Jin, Ning-De, 2017. "Characterization of flow pattern transitions for horizontal liquid–liquid pipe flows by using multi-scale distribution entropy in coupled 3D phase space," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 136-147.
    7. Palit, Sanjay K. & Mukherjee, Sayan, 2021. "A study on dynamics and multiscale complexity of a neuro system," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    8. He, Shaobo & Sun, Kehui & Wang, Huihai, 2016. "Multivariate permutation entropy and its application for complexity analysis of chaotic systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 812-823.
    9. Cui, Huizi & Zhou, Lingge & Li, Yan & Kang, Bingyi, 2022. "Belief entropy-of-entropy and its application in the cardiac interbeat interval time series analysis," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    10. Pastor, Marissa & Song, Juyong & Hoang, Danh-Tai & Jo, Junghyo, 2016. "Minimal perceptrons for memorizing complex patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 31-37.
    11. Liu, Yunxiao & Lin, Youfang & Wang, Jing & Shang, Pengjian, 2018. "Refined generalized multiscale entropy analysis for physiological signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 975-985.
    12. Fan, Xinghua & Li, Shasha & Tian, Lixin, 2016. "Complexity of carbon market from multi-scale entropy analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 79-85.
    13. Shupei Huang & Haizhong An & Xiangyun Gao & Meihui Jiang, 2016. "The Multiscale Fluctuations of the Correlation between Oil Price and Wind Energy Stock," Sustainability, MDPI, vol. 8(6), pages 1-14, June.
    14. Wu, Shuen-De & Wu, Chiu-Wen & Humeau-Heurtier, Anne, 2016. "Refined scale-dependent permutation entropy to analyze systems complexity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 454-461.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:465:y:2017:i:c:p:261-276. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.